Lingokids is a well-funded, fast-growing edtech startup changing the face of early childhood language education. We’ve taught over two million kids in 170 countries since our launch last year.
Are you ready to Playwork™ with us?
You should be a sharp, curious, and an autonomous fast-paced analytical individual who has a passion for going deep into data and understanding of how kids and parents use our service, and which are the opportunities to improve our product.
We currently have openings for Data Scientists in two squads: Product and Growth. Each position shares the description shown here plus some particular elements depending on the squad. We will try to place you in the track that best suits you but if you are interested in working in a particular problem space, please do let us know in the application process.
You will make your own cycle of data extraction, data analysis, data interpretation, summarizing data through presentations and visualizations, building Machine Learning models, putting them in production environments, providing insights, making recommendations, and communicating them to the team. Lingokids is still a fairly small company so we need out Data Scientists to be one-person armies.
You will also get to work on:
- Design, prototype, test, build and maintain ML models to fuel and sustain our company's goals and strategy. Those ML models will the core of a series of automatic decision-makers that will allow us to scale up.
- Communicate your insights to technical and non-technical audiences and being able to guide non-technical stakeholders to transform their ideas/needs into the appropriate deliverables. You need excellent communication and people skills.
- Generating relevant and clear insights, identify and clearly articulate recommendations drawn from data. Where can we make and impact? How can we add the most value? You are not only an executor but a guide.
- Make clear, attainable, and consistent definitions for all things data: metrics, data schemas, KPIs, etc. You will make sure we are able to understand each other.
- Work closely with the Data Engineering team to ensure the effectiveness and accuracy of our data to make sure all our data needs are being cover by our data infrastructure/ecosystem.
- Support deep ad-hoc analysis as: impact analysis, data inconsistencies investigation, experiment results interpretation, etc. Sometimes you will need to go deep, luckily, you are a scientist! : D
Which tools will you use?
Those that get the job done, period. We use a fairly common tech stack:
- Python/R for day to day tasks: analysis, modeling, productionisation, etc. Your code needs to be clean, understandable and efficient.
- AWS Redshift for our data warehousing, dbt for ELTing and SQL for querying the data. We use extensibly the AWS ecosystem (Sagemaker, ECS, Athena, etc.) so knowledge of these products is a plus.
- Notion for documentation and GitHub for version control.
- You should be familiar with most of those tools. However we are always open to adapt our ways to get the job done. The best idea/approach wins.
Are you our Senior Data Scientist?
We would like to meet you if you...
- Have a degree in mathematics, statistics, computer science or another quantitative discipline.
- Have experience developing advanced analytical solutions, using databases and analytics tools, ideally in a Startup environment, for at least 4 years.
- Have experience in the data extract, transform and load process including data cleansing and quality review.
- Have experience building statistical and machine learning (supervised/unsupervised) models, measuring their performance, extracting insights from them, and running them in production environments.
- Have proficiency with SQL and experience with R or Python and any data viz tool.
- Are always curious and enthusiastic about learning new analytical methods.
- Have worked with large volumes of data and have strong decision-making with imperfect information.
- Speak English fluently.